Abstract: Systems and methods are disclosed to implement a cyberattack detection system that monitors a computer network for lateral movement. In embodiments, the system uses network data from a computer network to build a baseline of connection behaviors for the network. Connection graphs are generated from new network data that indicate groups of nodes that made connections with one another during a last time interval. The graphs are analyzed for connection behavior anomalies and ranked to determine a subset of graphs with suspected lateral movement. Graphs with suspected lateral movement may be further analyzed to determine a set of possible attack paths in the lateral movements. The suspected attack paths are reported to network administrators via a notification interface. Advantageously, the disclosed system is able to detect potential lateral movements in localized portions of a network by monitoring for connection behavior anomalies in network data gathered from the network.

Abstract: Systems and methods are disclosed to implement a cyberattack detection system that monitors a computer network for lateral movement. In embodiments, the system uses network data from a computer network to build a baseline of connection behaviors for the network. Connection graphs are generated from new network data that indicate groups of nodes that made connections with one another during a last time interval. The graphs are analyzed for connection behavior anomalies and ranked to determine a subset of graphs with suspected lateral movement. Graphs with suspected lateral movement may be further analyzed to determine a set of possible attack paths in the lateral movements. The suspected attack paths are reported to network administrators via a notification interface. Advantageously, the disclosed system is able to detect potential lateral movements in localized portions of a network by monitoring for connection behavior anomalies in network data gathered from the network.

Abstract: Systems and methods are disclosed to implement a cyberattack detection system that monitors a computer network for lateral movement. In embodiments, the system uses network data from a computer network to build a baseline of connection behaviors for the network. Connection graphs are generated from new network data that indicate groups of nodes that made connections with one another during a last time interval. The graphs are analyzed for connection behavior anomalies and ranked to determine a subset of graphs with suspected lateral movement. Graphs with suspected lateral movement may be further analyzed to determine a set of possible attack paths in the lateral movements. The suspected attack paths are reported to network administrators via a notification interface. Advantageously, the disclosed system is able to detect potential lateral movements in localized portions of a network by monitoring for connection behavior anomalies in network data gathered from the network.